Design and Operation of a Multicarrier Energy System Based On Multi Objective Optimization Approach
Multi-energy systems will enhance the system
reliability and power quality. This paper presents an integrated
approach for the design and operation of distributed energy resources
(DER) systems, based on energy hub modeling. A multi-objective
optimization model is developed by considering an integrated view of
electricity and natural gas network to analyze the optimal design and
operating condition of DER systems, by considering two conflicting
objectives, namely, minimization of total cost and the minimization
of environmental impact which is assessed in terms of CO2
emissions. The mathematical model considers energy demands of the
site, local climate data, and utility tariff structure, as well as technical
and financial characteristics of the candidate DER technologies. To
provide energy demands, energy systems including photovoltaic, and
co-generation systems, boiler, central power grid are considered. As
an illustrative example, a hotel in Iran demonstrates potential
applications of the proposed method. The results prove that
increasing the satisfaction degree of environmental objective leads to
increased total cost.
[1] Miah, M.S., N.U. Ahmed, and M. Chowdhury, Optimum policy for
integration of renewable energy sources into the power generation
system. Energy Economics, 2012. 34(2): p. 558-567.
[2] Moss, D.L., Kwoka, J.E. Competition policy and the transition to a lowcarbon,
efficient electricity industry. The Electricity Journal. 2010 23 (7)
[3] Iran's Energy Balance, 2010, Institute for International Energy Studies
Affiliated to Ministry of Petroleum, I.R. Iran
[4] CO2 Emissions from Fuel Combustion 2012, International Energy
Agency
[5] Mehleri, E.D., et al., Optimal design and operation of distributed energy
systems: Application to Greek residential sector. Renewable Energy,
2013. 51(0): p. 331-342
[6] Akorede MF, Hizam H, Rouresmaeil E. Distributed energy resources
and benefits to the environment. Renewable and Sustainable Energy
Reviews 2010; 14:724e34.
[7] Alanne, K. and A. Saari, Distributed energy generation and sustainable
development. enewable and Sustainable Energy Reviews, 2006. 10(6):
p. 539-558
[8] Carley S. Distributed generation: an empirical analysis of primary
motivators. Energy Policy 2009; 37:1648e59.
[9] Hiremath RB, Shikha S, Ravindranath NH. Decentralised energy
planning: Modeling and application-a review. Renewable and
Sustainable Energy Reviews 2007; 11:729e52.
[10] Siddiqui AS, Firestone R, Ghosh S, Stadler M, Edwards JL, Marnay C.
Distributed energy resources customer adoption modeling with
combined heat and power applications. LBNL-52718; 2003.
[11] Heatmap manual. Washington State University; 2002.
[12] Georgilakis, P.S., State-of-the-Art of Decision Support Systems for the
Choice of Renewable Energy Sources for Energy Supply in Isolated
Regions. International Journal of Distributed Energy Resources, 2006.
Volume 2 (Number 2): p. Pages 129-150.
[13] Hafez, O. and K. Bhattacharya, Optimal planning and design of a
renewable energy based supply system for microgrids. Renewable
Energy. 45(0): p. 7-15.
[14] Moghaddas-Tafreshi, S.M., H.A. Zamani, and S.M. Hakimi, Optimal
sizing of distributed resources in micro grid with loss of power supply
probability technology by using breeding particle swarm optimization.
Journal of Renewable and Sustainable Energy, 2011. 3(4): p. 043105-17.
[15] Handschin E, Neise F, Neumann H, Schultz R. Optimal operation of
dispersed generation under uncertainty using mathematical
programming. International Journal of Electrical Power and Energy
Systems 2006; 28:618e26.
[16] Ren H, Gao W. A MILP model for integrated plan and evaluation of
distributed energy systems. Applied Energy 2010; 87:1001e14.
[17] Giannakoudis G, Papadopoulos AI, Seferlis P, Voutetakis S. "Optimum
design and operation under uncertainty of power systems using
renewable energy sources and hydrogen storage." International Journal
of Hydrogen Energy 2010; 35:872–891.
[18] Geidl, Martin, et al. "The Energy Hub–A powerful concept for future
energy systems." Third annual Carnegie Mellon Conference on the
Electricity Industry, Pittsburgh. 2007.
[19] Geidl, Martin, and GöranAndersson. "Optimal power flow of multiple
energy carriers." Power Systems, IEEE Transactions on 22.1 (2007):
145-155.
[20] Geidl, Martin, et al. "Energy hubs for the future." IEEE Power and
Energy Magazine 5.1 (2007): 24-30.
[21] Geidl, Martin, and Göran Andersson. "A modeling and optimization
approach for multiple energy carrier power flow." Power Tech, 2005
IEEE Russia. IEEE, 2005.
[22] Nazar, MehrdadSetayesh, and Mahmood R. Haghifam. "Multiobjective
electric distribution system expansion planning using hybrid energy hub
concept." Electric Power Systems Research 79.6 (2009): 899-911.
[23] Schulze, M., L. Friedrich, and M. Gautschi. "Modeling and optimization
of renewables: applying the energy hub approach." Sustainable Energy
Technologies, 2008. ICSET 2008. IEEE International Conference on.
IEEE, 2008.
[24] Marler, R. T. and J. S. Arora. "Survey of multi-objective optimization
methods for engineering." Structural and multidisciplinary optimization
2004, 26(6): 369-395
[25] D&R, Buildings Energy Data Book, D&R International, Ltd., 2009
[26] R. Graham, W. Chow, Technical and Economic Assessment of
Combined Heat and Power Technologiesfor Commercial Customer
Applications, EPRI Project Manager, 2003.
[27] Weber C, Shah N. Optimisation based design of a district energy system
for an eco-town in the United Kingdom. Energy 2011; 36:1292e308.
[28] Farid Seyyedeyn, Azadeh MaroufMashat, Ramin Roshandel, Sourena
Sattrai, Optimal design and operation of Photovoltaic-electrolyzer
system using particle swarm optimization, the International journal of
Sustainable energy, published online , April 2014
[1] Miah, M.S., N.U. Ahmed, and M. Chowdhury, Optimum policy for
integration of renewable energy sources into the power generation
system. Energy Economics, 2012. 34(2): p. 558-567.
[2] Moss, D.L., Kwoka, J.E. Competition policy and the transition to a lowcarbon,
efficient electricity industry. The Electricity Journal. 2010 23 (7)
[3] Iran's Energy Balance, 2010, Institute for International Energy Studies
Affiliated to Ministry of Petroleum, I.R. Iran
[4] CO2 Emissions from Fuel Combustion 2012, International Energy
Agency
[5] Mehleri, E.D., et al., Optimal design and operation of distributed energy
systems: Application to Greek residential sector. Renewable Energy,
2013. 51(0): p. 331-342
[6] Akorede MF, Hizam H, Rouresmaeil E. Distributed energy resources
and benefits to the environment. Renewable and Sustainable Energy
Reviews 2010; 14:724e34.
[7] Alanne, K. and A. Saari, Distributed energy generation and sustainable
development. enewable and Sustainable Energy Reviews, 2006. 10(6):
p. 539-558
[8] Carley S. Distributed generation: an empirical analysis of primary
motivators. Energy Policy 2009; 37:1648e59.
[9] Hiremath RB, Shikha S, Ravindranath NH. Decentralised energy
planning: Modeling and application-a review. Renewable and
Sustainable Energy Reviews 2007; 11:729e52.
[10] Siddiqui AS, Firestone R, Ghosh S, Stadler M, Edwards JL, Marnay C.
Distributed energy resources customer adoption modeling with
combined heat and power applications. LBNL-52718; 2003.
[11] Heatmap manual. Washington State University; 2002.
[12] Georgilakis, P.S., State-of-the-Art of Decision Support Systems for the
Choice of Renewable Energy Sources for Energy Supply in Isolated
Regions. International Journal of Distributed Energy Resources, 2006.
Volume 2 (Number 2): p. Pages 129-150.
[13] Hafez, O. and K. Bhattacharya, Optimal planning and design of a
renewable energy based supply system for microgrids. Renewable
Energy. 45(0): p. 7-15.
[14] Moghaddas-Tafreshi, S.M., H.A. Zamani, and S.M. Hakimi, Optimal
sizing of distributed resources in micro grid with loss of power supply
probability technology by using breeding particle swarm optimization.
Journal of Renewable and Sustainable Energy, 2011. 3(4): p. 043105-17.
[15] Handschin E, Neise F, Neumann H, Schultz R. Optimal operation of
dispersed generation under uncertainty using mathematical
programming. International Journal of Electrical Power and Energy
Systems 2006; 28:618e26.
[16] Ren H, Gao W. A MILP model for integrated plan and evaluation of
distributed energy systems. Applied Energy 2010; 87:1001e14.
[17] Giannakoudis G, Papadopoulos AI, Seferlis P, Voutetakis S. "Optimum
design and operation under uncertainty of power systems using
renewable energy sources and hydrogen storage." International Journal
of Hydrogen Energy 2010; 35:872–891.
[18] Geidl, Martin, et al. "The Energy Hub–A powerful concept for future
energy systems." Third annual Carnegie Mellon Conference on the
Electricity Industry, Pittsburgh. 2007.
[19] Geidl, Martin, and GöranAndersson. "Optimal power flow of multiple
energy carriers." Power Systems, IEEE Transactions on 22.1 (2007):
145-155.
[20] Geidl, Martin, et al. "Energy hubs for the future." IEEE Power and
Energy Magazine 5.1 (2007): 24-30.
[21] Geidl, Martin, and Göran Andersson. "A modeling and optimization
approach for multiple energy carrier power flow." Power Tech, 2005
IEEE Russia. IEEE, 2005.
[22] Nazar, MehrdadSetayesh, and Mahmood R. Haghifam. "Multiobjective
electric distribution system expansion planning using hybrid energy hub
concept." Electric Power Systems Research 79.6 (2009): 899-911.
[23] Schulze, M., L. Friedrich, and M. Gautschi. "Modeling and optimization
of renewables: applying the energy hub approach." Sustainable Energy
Technologies, 2008. ICSET 2008. IEEE International Conference on.
IEEE, 2008.
[24] Marler, R. T. and J. S. Arora. "Survey of multi-objective optimization
methods for engineering." Structural and multidisciplinary optimization
2004, 26(6): 369-395
[25] D&R, Buildings Energy Data Book, D&R International, Ltd., 2009
[26] R. Graham, W. Chow, Technical and Economic Assessment of
Combined Heat and Power Technologiesfor Commercial Customer
Applications, EPRI Project Manager, 2003.
[27] Weber C, Shah N. Optimisation based design of a district energy system
for an eco-town in the United Kingdom. Energy 2011; 36:1292e308.
[28] Farid Seyyedeyn, Azadeh MaroufMashat, Ramin Roshandel, Sourena
Sattrai, Optimal design and operation of Photovoltaic-electrolyzer
system using particle swarm optimization, the International journal of
Sustainable energy, published online , April 2014
@article{"International Journal of Earth, Energy and Environmental Sciences:53164", author = "Azadeh Maroufmashat and Sourena Sattari Khavas and Halle Bakhteeyar", title = "Design and Operation of a Multicarrier Energy System Based On Multi Objective Optimization Approach", abstract = "Multi-energy systems will enhance the system
reliability and power quality. This paper presents an integrated
approach for the design and operation of distributed energy resources
(DER) systems, based on energy hub modeling. A multi-objective
optimization model is developed by considering an integrated view of
electricity and natural gas network to analyze the optimal design and
operating condition of DER systems, by considering two conflicting
objectives, namely, minimization of total cost and the minimization
of environmental impact which is assessed in terms of CO2
emissions. The mathematical model considers energy demands of the
site, local climate data, and utility tariff structure, as well as technical
and financial characteristics of the candidate DER technologies. To
provide energy demands, energy systems including photovoltaic, and
co-generation systems, boiler, central power grid are considered. As
an illustrative example, a hotel in Iran demonstrates potential
applications of the proposed method. The results prove that
increasing the satisfaction degree of environmental objective leads to
increased total cost.
", keywords = "Multi objective optimization, DER systems, Energy
hub, Cost, CO2 emission.", volume = "8", number = "9", pages = "622-6", }
